Data skipping skips unnecessary processing of irrelevant or duplicate data, loading only the information that needs to be analyzed. Specifically, data skipping refers to scanning a column (or table) to find rows that qualify for a given query and skip over data that doesn't qualify for your query. When skipping irrelevant data, the irrelevant data is not read into memory from disk and CPU resources are not demanded to find out why those irrelevant rows/columns are not needed in the first place.
Data compression involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying unnecessary information and removing it. Compression is useful as it helps reduce resource usage, such as data storage space or transmission capacity.